research-article

Real-Time Optimization of Web Publisher RTB Revenues

Authors:

Pedro Chahuara,

Nicolas Grislain,

Gregoire Jauvion,

Jean-Michel RendersAuthors Info & Claims

KDD '17: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Pages 1743 - 1751

https://doi.org/10.1145/3097983.3098150

Published: 13 August 2017 Publication History

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Abstract

This paper describes an engine to optimize web publisher revenues from second-price auctions. These auctions are widely used to sell online ad spaces in a mechanism called real-time bidding (RTB). Optimization within these auctions is crucial for web publishers, because setting appropriate reserve prices can significantly increase revenue. We consider a practical real-world setting where the only available information before an auction occurs consists of a user identifier and an ad placement identifier. The real-world challenges we had to tackle consist mainly of tracking the dependencies on both the user and placement in an highly non-stationary environment and of dealing with censored bid observations. These challenges led us to make the following design choices: (i) we adopted a relatively simple non-parametric regression model of auction revenue based on an incremental time-weighted matrix factorization which implicitly builds adaptive users' and placements' profiles; (ii) we jointly used a non-parametric model to estimate the first and second bids' distribution when they are censored, based on an on-line extension of the Aalen's Additive model.

Our engine is a component of a deployed system handling hundreds of web publishers across the world, serving billions of ads a day to hundreds of millions of visitors. The engine is able to predict, for each auction, an optimal reserve price in approximately one millisecond and yields a significant revenue increase for the web publishers.

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Cited By

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Zhang LZhang XWang YLi XDong ZXu J(2025)Adapting Constrained Markov Decision Process for OCPC Bidding with Delayed ConversionsACM Transactions on Information Systems10.1145/370642043:2(1-29)Online publication date: 18-Jan-2025
https://dl.acm.org/doi/10.1145/3706420
Kalra AWang CBorcea CChen Y(2023)Reserve Price optimization in First-Price Auctions via Multi-Task Learning2023 IEEE International Conference on Data Mining (ICDM)10.1109/ICDM58522.2023.00029(200-209)Online publication date: 1-Dec-2023
https://doi.org/10.1109/ICDM58522.2023.00029
Ishfaq UShabbir DKhan JKhan HNaseer SIrshad AShafiq MHamam H(2022)Empirical Analysis of Machine Learning Algorithms for Multiclass PredictionWireless Communications & Mobile Computing10.1155/2022/74511522022Online publication date: 30-Mar-2022
https://dl.acm.org/doi/10.1155/2022/7451152
Show More Cited By

Index Terms

Real-Time Optimization of Web Publisher RTB Revenues
1. Applied computing
  1. Electronic commerce
    1. Online auctions
2. Mathematics of computing
  1. Probability and statistics

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Published In

KDD '17: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 2017

2240 pages

ISBN:9781450348874

DOI:10.1145/3097983

General Chairs:
Stan Matwin
Dalhousie University
,
Shipeng Yu
LinkedIn
,
Faisal Farooq
IBM

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 13 August 2017

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ANR (Agence Nationale de la Recherche)

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KDD '17

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KDD '17: The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 13 - 17, 2017

NS, Halifax, Canada

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KDD '17 Paper Acceptance Rate 64 of 748 submissions, 9%;

Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining

August 3 - 7, 2025

Toronto , ON , Canada

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Cited By

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Zhang LZhang XWang YLi XDong ZXu J(2025)Adapting Constrained Markov Decision Process for OCPC Bidding with Delayed ConversionsACM Transactions on Information Systems10.1145/370642043:2(1-29)Online publication date: 18-Jan-2025
https://dl.acm.org/doi/10.1145/3706420
Kalra AWang CBorcea CChen Y(2023)Reserve Price optimization in First-Price Auctions via Multi-Task Learning2023 IEEE International Conference on Data Mining (ICDM)10.1109/ICDM58522.2023.00029(200-209)Online publication date: 1-Dec-2023
https://doi.org/10.1109/ICDM58522.2023.00029
Ishfaq UShabbir DKhan JKhan HNaseer SIrshad AShafiq MHamam H(2022)Empirical Analysis of Machine Learning Algorithms for Multiclass PredictionWireless Communications & Mobile Computing10.1155/2022/74511522022Online publication date: 30-Mar-2022
https://dl.acm.org/doi/10.1155/2022/7451152
Kalra AWang CBorcea CChen YTeredesai AKumar VLi YRosales RTerzi EKarypis G(2019)Reserve Price Failure Rate Prediction with Header Bidding in Display AdvertisingProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330729(2819-2827)Online publication date: 25-Jul-2019
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Rhuggenaath JAkcay AZhang YKaymak U(2019)Fuzzy Logic based Pricing combined with Adaptive Search for Reserve Price Optimization in Online Ad Auctions2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)10.1109/FUZZ-IEEE.2019.8858975(1-8)Online publication date: 23-Jun-2019
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Rhuggenaath JAkcay AZhang YKaymak U(2019)Optimizing reserve prices for publishers in online ad auctions2019 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr)10.1109/CIFEr.2019.8759123(1-8)Online publication date: May-2019
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Rhuggenaath JAkcay AZhang YKaymak U(2019)A PSO-based Algorithm for Reserve Price Optimization in Online Ad Auctions2019 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2019.8789915(2611-2619)Online publication date: 10-Jun-2019
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Jauvion GGrislain NGuo YFarooq F(2018)Optimal Allocation of Real-Time-Bidding and Direct CampaignsProceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3219819.3219877(416-424)Online publication date: 19-Jul-2018
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Optimization of a SSP's Header Bidding Strategy using Thompson Sampling

Optimal Allocation of Real-Time-Bidding and Direct Campaigns

The Impact of Discrete Bidding and Bidder Aggressiveness on Sellers' Strategies in Open English Auctions: Reserves and Covert Shilling

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